DbET: Execution Time Distribution-based Plan Selection

Abstract

While selecting the execution plan for a given query based on a single estimated cost is a generally-adopted strategy, it is usually error-prone and fails to comprehensively profile the plan performance. In this work, we complement existing plan selection methods by proposing a new approach named ET, which produces execution time distributions for query plans utilizing conformal predictions. We develop dbET, a framework that integrates ET into an existing DBMS, requiring no modification to the DBMS and only incurring minor overhead to query processing. Based on the execution time distribution, we design several intuitive yet fundamental query execution objectives and devise the corresponding plan selection strategies. Our experiments on several widely-adopted benchmarks showcase that our design significantly improves the capability of DBMSs in achieving the designated objectives.